Koagne Longpa Tamo Silas | Analog Artificial Neural Networks | Innovative Research Award

Posted on by Best Paper Award

Mr. Koagne Longpa Tamo Silas | Analog Artificial Neural Networks | Innovative Research Award

Doctoral Researcher at University of Dschang, Cameroon.

Koagne Longpa Tamo Silas is a Ph.D. student in Physics at Dschang State University, Cameroon, with a specialization in Medical Physics and Embedded Systems. He holds an M.Sc. in Physics (Electronics) from Dschang State University and a DIPET 2 in Electronics from the Higher Technical Teacher Training College, University of Bamenda. With a strong foundation in artificial neural networks, analog electronics, and microcontroller programming, his research focuses on integrating automation and AI in medical physics. In addition to his research, he has extensive teaching experience in electronics and computer science at various technical institutions in Cameroon. His industrial expertise includes electronic circuit design, electrical network maintenance, and embedded system applications.

Publication Profile

Google Scholar

Educational Details

Mr. Koagne Longpa Tamo Silas is currently a Ph.D. student in Physics at Dschang State University, Cameroon, specializing in Medical Physics, where he has been enrolled since December 2022. He previously obtained an M.Sc. in Physics (Electronics) from Dschang State University in July 2022, with a thesis on the Specification and Implementation of Multilayer Perceptron Analog Artificial Neural Networks, under the supervision of Dr. Djimeli Tsajio Alain B. His B.Sc. in Physics was completed in August 2021 at the same university.

Before his graduate studies, he pursued technical education at the Higher Technical Teacher Training College, University of Bamenda, earning:

  • DIPET 2 in Electronics (July 2020) with a dissertation on Digital Breath Alcohol Detection System with SMS Alert and Vehicle Tracking on Google Maps, supervised by Prof. Nfah Mbaka Eutace and Dr. Kamdem Kuate Paul Didier.

  • DIPET 1 in Electronics (August 2018) with a dissertation on Electronic Attendance System Based on RFID with Automatic Door Unit, supervised by Mr. Kouam Jules.

He also holds a GCE Advanced Level (5 papers, 2015) and a GCE Ordinary Level (8 papers, 2013) from Government Bilingual High School Mbouda. His academic journey began at École Primaire Bilingue de la Promotion Mbouda, where he obtained his First School Leaving Certificate (FSLC) in 2008.

Professional Experience

Mr. Silas has extensive experience in academia and industry. He has been an Electronics Teacher at Government Technical College Ngombo-ku, Cameroon, since January 2021, where he instructs students in circuit design, microcontrollers, and automation. He previously served as a Junior Lecturer in Computer Science at Higher Technical Teacher Training College, Bambili (2019-2020) and an Electronics Teacher at Government Technical High School Bambui (2017-2018).

His industrial experience includes:

  • HYTECHS-Yaoundé, Cameroon (2019) – Worked on maintenance of HP INKJET and RICOH printers, electronic printing device repairs, and installation of printing equipment. Supervised by Mr. Nkuimen Tankeu Cedric.

  • MEECH CAM Sarl-Yaoundé, Cameroon (2016) – Focused on underground electric cable installation, maintenance of high-voltage network devices, and electrical network line installation. Supervised by Mr. Ndjegnia Franck Enrico.

Research Interest

  • Analog Artificial Neural Networks

  • Digital and Analog Electronics

  • Embedded Systems and Microcontroller Programming

  • Circuit Simulation (SPICE, Cadence Virtuoso)

  • Electronic Design Automation (EDA)

  • Analog Signal Processing

  • Electronics and Communication Systems

Author Metrics

Mr. Silas is an emerging researcher in Medical Physics and Electronics, contributing to research on artificial neural networks, embedded systems, and medical automation. His work has been supervised by esteemed faculty at Dschang and Bamenda universities. As he advances in his Ph.D. studies, his publications and contributions to the field are expected to grow in impact within scientific and engineering communities.

Top Noted Publication

1. A High-Resolution Non-Volatile Floating Gate Transistor Memory Cell for On-Chip Learning in Analog Artificial Neural Networks

  • Authors: KLT Silas, DTA Bernard, FT Bernard, L Jean-Pierre, GW Ejuh

  • Year: 2025

  • Research Focus:
    This paper presents the design and implementation of a high-resolution, non-volatile floating gate transistor memory cell, optimized for on-chip learning in analog artificial neural networks (ANNs). The study focuses on developing efficient, low-power, and high-precision memory architectures tailored for ANN applications, particularly in medical diagnostics and real-time data processing.

2. Breast Cancer Diagnosis with Machine Learning Using Feed-Forward Multilayer Perceptron Analog Artificial Neural Network

  • Authors: B Djimeli-Tsajio Alain, KLT Silas, LT Jean-Pierre, N Thierry, GW Ejuh

  • Year: 2024

  • Research Focus:
    This study explores the application of feed-forward multilayer perceptron (MLP) analog artificial neural networks (ANNs) for breast cancer diagnosis. The model utilizes machine learning techniques to enhance diagnostic accuracy, reducing false positives and false negatives in mammography analysis. The findings demonstrate the potential of ANN-based medical imaging solutions in early cancer detection and precision medicine.

3. Design and Implementation of a Digital Breath Alcohol Detection System with SMS Alert and Vehicle Tracking on Google Map

  • Author: KLT Silas

  • Year: 2020

  • Research Focus:
    This project details the development of a digital breath alcohol detection system that integrates an SMS alert mechanism and real-time vehicle tracking using Google Maps. The system is designed to improve road safety by detecting alcohol levels in drivers and alerting authorities or emergency contacts. The integration of embedded systems, microcontrollers, and GPS technology makes it a valuable tool for transportation safety enforcement.

4. Design and Realization of an Electronic Attendance System Based on RFID with an Automatic Door Unit

  • Author: MK Jules

  • Contributor: KLT Silas

  • University: University of Bamenda

  • Year: 2018

  • Research Focus:
    This paper presents an RFID-based electronic attendance system with an automatic door control unit, aimed at enhancing security and automation in institutional environments. The system automatically logs student or staff attendance and grants access based on RFID authentication, improving accuracy and eliminating manual attendance tracking.

Conclusion

Mr. Koagne Longpa Tamo Silas is a strong candidate for the Innovative Research Award due to his pioneering work in analog artificial neural networks, medical AI applications, and embedded systems. His contributions to AI-driven medical diagnostics and ANN memory design demonstrate a forward-thinking approach to AI and electronics integration.

To further strengthen his candidacy, publishing in high-impact journals, increasing citations, pursuing patents, and collaborating on interdisciplinary AI projects would enhance the global impact of his work. Nonetheless, his innovative research in analog ANNs and automation technologies makes him a deserving nominee for this award.

 

 

Priyanka Das | Autonomous systems | Best Researcher Award

Posted on by Best Paper Award

Ms. Priyanka Das | Autonomous systems | Best Researcher Award

Manufacturing Engineer at Ford Motor company

Summary:

Priyanka Das is a skilled robotics and controls engineer with expertise in autonomous systems, manufacturing automation, and advanced robotics. Currently a Manufacturing Controls Engineer at Ford Motor Company, she has previously contributed to innovative automation solutions at Tesla. A researcher and thought leader, Priyanka has authored multiple publications in controls engineering and localization techniques. Her technical acumen, combined with her passion for community engagement and STEM advocacy, underscores her commitment to advancing technology and empowering the next generation of engineers.

Professional Profile:

👩‍🎓Education:

Priyanka Das holds a Master of Engineering in Electrical Engineering, with a major in Robotics, from the University of Cincinnati (2019–2021). During her studies, she specialized in advanced topics such as Autonomous Vehicle (AV) Navigation and Controls, Simultaneous Localization and Mapping (SLAM), Kalman and Particle Filters, and Robot Operating System (ROS). She was awarded the prestigious Graduate Incentive Award (GIA) valued at $10,640 USD. Priyanka also earned her Bachelor of Technology in Electrical and Electronics Engineering from Vellore Institute of Technology, India (2015–2019), where she actively participated as a student representative and served as captain of the women’s sports team.

Professional Experience:

Priyanka is an accomplished engineer with experience in controls, robotics, and automation across leading organizations. She currently works as a Manufacturing Controls Engineer at Ford Motor Company (April 2024–Present), where she oversees the implementation and validation of assembly and machining controls for global Powertrain Operations (PTO) programs. Her responsibilities include leading engineering meetings, driving cross-functional collaboration with Tier I suppliers, and delivering new model programs across plants worldwide.

Previously, Priyanka worked as a Controls Engineer at Tesla Inc. (November 2021–February 2024). There, she developed automation programs for inverter and battery manufacturing lines, optimized robotic processes for improved production efficiency, and debugged control systems using advanced tools like Beckhoff and Siemens PLCs. She has also contributed to path-planning research and quadcopter localization as a volunteer Guided Navigation and Control Researcher at the University of Cincinnati’s RISC Lab. Earlier, she interned at the Tarapur Atomic Power Station, India, assisting with testing and calibration of power generation equipment and developing solutions for smart power management.

Research Interests:

Priyanka’s research interests lie in autonomous systems, advanced robotics, and controls engineering. She has a particular focus on developing robust localization techniques, path-planning algorithms, and machine learning models for GPS-denied environments. Her expertise spans fields like Sensor Fusion, SLAM, PID, and LQR controls.

Author Metrics and Awards

Priyanka Das has authored five research papers with significant contributions to the fields of robotics, controls engineering, and autonomous systems. Her work has been published in reputed journals like IJIRMPS and IJCEM, and her research is widely referenced in the academic community.

Top Noted Publication:

1. Optimizing Sensor Integration for Enhanced Localization in Underwater ROVs

  • Publication: International Journal of Scientific Research in Engineering and Management
  • Publication Date: December 26, 2024
  • DOI: 10.55041/ijsrem10901
  • Author(s): Priyanka Das
  • Summary:This study presents an optimized approach for integrating multiple sensors to enhance localization accuracy in remotely operated underwater vehicles (ROVs). It explores sensor fusion techniques, error mitigation strategies, and real-time localization improvements using AI-based models.

2. A Comparative Study of Kalman Filters and Particle Filters for Localization in Dynamic Settings for SLAM in Unknown Environments

  • Publication Type: Dataset
  • DOI: 10.5281/zenodo.14498207
  • Author(s): Priyanka Das
  • Summary:This dataset provides a comparative analysis of Kalman Filters and Particle Filters in dynamic environments, focusing on their performance in Simultaneous Localization and Mapping (SLAM) for robots operating in unknown terrains.

3. Advancing Simultaneous Localization and Mapping (SLAM) for Robots in Unstructured Terrain

  • Publication: Journal article
  • DOI: 10.36948/ijfmr.2020.v02i06.25432
  • Author(s): Priyanka Das
  • Summary:This paper investigates the latest advancements in SLAM techniques for robotic navigation in unstructured and unpredictable environments, with an emphasis on sensor fusion, real-time mapping, and adaptive algorithms.

4. Case Studies in ROV Development: Innovations in Underwater Exploration Technology

  • Publication Type: Dataset
  • DOI: 10.5281/zenodo.14434005
  • Author(s): Priyanka Das
  • Summary:A collection of case studies highlighting recent innovations in remotely operated vehicle (ROV) technology, including sensor integration, autonomy, and deep-sea exploration capabilities.

5. Challenges in Designing Motors for Remotely Operated Underwater Vehicles: A Focus on Hydrodynamics

  • Publication Type: Report
  • DOI: 10.5281/zenodo.14538286
  • Author(s): Priyanka Das
  • Summary:This report discusses the hydrodynamic challenges involved in designing efficient motors for underwater ROVs, examining propulsion efficiency, power consumption, and environmental factors affecting performance.

Conclusion:

Priyanka Das is an exceptional candidate for the Best Researcher Award, with notable strengths in impactful research, technical innovation, and industry experience. Her work in advanced robotics and FSS technology has made significant contributions to academia and industry alike. While there is room to expand her publication base and professional recognition, her dedication to engineering excellence and STEM advocacy makes her a strong contender for the award.